Data Scientist developing statistical and machine learning algorithms to detect bots and fraud. Supporting HUMAN Security’s platform that protects enterprises and internet platforms from cybercrime.
Responsibilities
Research and develop algorithms to detect bots and fight fraud
Support the full cycle of fraud fighting, from gathering business requirements and exploratory research through production deployment of statistical detection techniques
Partner with Product, Engineering, and Analysts to improve bot detection
Build competitive product features and optimize data and machine learning infrastructure
Research and experiment with detection frameworks in cybersecurity and fraud, statistical techniques, and ML tooling
Support data science standards and best practices in detection and modeling
Review other data scientists’ work before launching detection rules and algorithms
Participate in anomaly monitoring ('sheriffing') and tech-debt days
Develop software tooling and automation to accelerate fraud detection and automate cumbersome tasks
Requirements
Experience solving large-scale, data-intensive problems in production systems
Literacy with large datasets
Ability to explain statistical modeling approaches and select appropriate methods
Engineering awareness of shipping working code to customers
Fluency with Python and SQL
Familiarity with related tools, libraries, and platforms
Fluency in object-oriented development
Strong debugging skills
Experience working on cross-functional projects with multiple technical and non-technical stakeholders
Following SDLC best practices, including project management, version control, unit testing, and CI/CD
Benefits
Comprehensive total rewards package
Well-being stipends
Learning stipends
Flexible work options
Dedicated time off
Stock options and other incentive pay may be provided
Medical, financial, and/or other benefits, depending on the position offered
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